About Me
AI product engineer with more than three years of experience turning business goals into working software. Work spans product definition, solution design, and hands-on engineering, with a focus on agentic systems and enterprise delivery. Strongest at the start of complex projects: clarifying the problem, designing the system, and guiding AI-assisted implementation through review and testing.
Core Competencies
AI & Agentic Systems
Agent orchestration, RAG, MCP, tool use, prompt optimisation, structured outputs, LLM evaluation, guardrails, multi-agent patterns.
Product & Engineering
Solution architecture, domain modelling, TypeScript, React, Python, Django, FastAPI, RBAC, multi-tenancy.
Delivery & Quality
Requirements discovery, backlog planning, enterprise delivery, automated testing, stakeholder communication, technical documentation.
Technical Stack
Languages & Backend
Python, TypeScript, JavaScript, SQL, Go, Django REST Framework, Pydantic, Celery, Redis, PostgreSQL, REST/OpenAPI.
Frontend & Extensions
React, TanStack Query, Zustand, Tailwind CSS, Chart.js, Chrome/Edge Manifest V3, service workers.
Cloud, Security & Quality
Docker, GitHub Actions, GCP (Cloud Run, Cloud SQL, Artifact Registry, Secret Manager), OAuth 2.0, OIDC, SAML, SSO, pytest, Playwright, Vitest.
Education
2023 BSc Computer Science, Distance-Learning University
Professional Experience
- Help shape and build an enterprise platform for understanding and managing AI usage and cost.
- Turn product and customer needs into clear user journeys, data models, and access rules.
- Build React and TypeScript dashboard features and browser integrations for analytics, administration, onboarding, and policy controls.
- Contribute Django backend features for multi-tenant access control, authentication, and reliable event processing.
- Use agentic development methods to plan work, manage context, and review generated code against acceptance criteria and automated tests.
- Built the original marketing website and maintain product documentation and development guidance.
Focus: Enterprise AI cost & usage platform: React, TypeScript, Django, multi-tenant RBAC, browser integrations, agentic delivery.
- Progressed from junior developer into senior software development and leadership of the AI team.
- Worked with clients to understand needs, then produced solution designs, backlogs, and delivery timelines with engineering, product, infrastructure, and security.
- Planned and built configurable AI workflow systems using retrieval, tool integration, and role-based access.
- Built backend and user interface features for RBAC in multi-tenant systems.
- Led technical planning and delivery for enterprise clients from discovery through implementation.
- Built a predictive modelling proof of concept using a custom operational dataset to support schedule forecasting.
- Improved reliability, automated tests, and documentation for AI workflow systems; created reusable agent skills for the development team.
- Interviewed engineering candidates and supported customer discovery, product demonstrations, sales conversations, and industry events.
Focus: Enterprise AI workflow systems: RAG, tool integration, RBAC, multi-tenancy, predictive modelling, client delivery and pre-sales.